Friday, February 28, 2020 from Noon to 12:50pm
MMRB - 1013, Off-Campus
Sunduz Keles, Ph.D.
Department of Biostatistics & Medical Informatics and Department of Statistics
University of Wisconsin
Hi-C assays are currently state-of-the-art for mapping long-range chromatin interactions genome-wide and data from these assays are now being routinely used to interpret results from genome-wide association studies. I will present two methods that we have developed for addressing critical needs in the analysis of Hi-C Data: mHi-C for leveraging multi-mapping reads and FreeHi-C for simulating realistic Hi-C data for benchmarking and data augmentation. In the second part of the talk, I will introduce atSNP Search which provides statistical evaluation of impact of SNPs on transcription factor-DNA interactions (atSNP Search: http://atsnp.biostat.wisc.edu/).